Mellin Transform-Based Correction Method for Linear Scale Inconsistency of Intrusion Events Identification in OFPS
For the problem that the linear scale of intrusion signals in the optical fiber pre-warning system (OFPS) is inconsistent, this paper presents a method to correct the scale. Firstly, the intrusion signals are intercepted, and an aggregate of the segments with equal length is obtained. Then, the Mellin transform (MT) is applied to convert them into the same scale. The spectral characteristics are obtained by the Fourier transform. Finally, we adopt back-propagation (BP) neural network to identify intrusion types, which takes the spectral characteristics as input. We carried out the field experiments and collected the optical fiber intrusion signals which contain the picking signal, shoveling signal, and running signal. The experimental results show that the proposed algorithm can effectively improve the recognition accuracy of the intrusion signals.
KeywordsLinear scale OFPS MT BP neural network spectral characteristics
This work was supported by the National Natural Science Foundation of China (Grant Nos. 61571014 and 61601006); Beijing Nature Science Foundation (Grant No. 4172017); General Project of Science and Technology Program of Beijing Education Commission (Grant No. KM201610009004).
- K. Liu, T. J. Chai, T. G. Liu, J. F. Jiang, Q. N. Chen, L. Pan, et al. , “Multi-area optical perimeter security system with quick invasion judgement algorithm,” Journal of Optoelectronics Laser, 2015, 26(2): 288–294.Google Scholar
- C. H. Zhu, Y. Z. Qu, and J. P. Wang, “The vibration signal recognition of optical fiber perimeter based on time-frequency features,” Opto-Electronic Engineering, 2014, 41(1): 16–22.Google Scholar
- L. Wang, Y. B. Guo, T. G. Sun, J. Y. Huo, and L. Zhang, “Signal recognition of the optical fiber vibration sensor based on two-level feature extraction,” in Proceeding of IEEE 8th International Congress on Image and Signal, Shenyang, China, 2015, pp: 1484–1488.Google Scholar
- Z. Y. Wang, Z. Q. Pan, Q. Ye, H. W. Cai, R. H. Qu, and Z. J. Fang, “Fast pattern recognition based on frequency spectrum analysis used for intrusion alarming in optic fiber fence,” Chinese Journal of Lasers, 2015, 42(4): 1–6.Google Scholar
- H. F. Li, X. D. Yin, J. Z. Liu, C. Z. Zhang, and Y. Chen, “Intrusion signal recognition basing on optical fiber Bragg grating vibration sensor,” Optical Communication Technology, 2012, 2: 12–14.Google Scholar
- X. C. Dai and Q. Xie, “Research on image matching algorithm based on Fourier-Mellin transform,” Infrared Technology, 2016, 38(10): 860–863.Google Scholar
- S. W. Zhang, S. C. Zhen, X. L. Zhao, and S. T. Zhao, “Recognition method of radar target using range profile,” Systems Engineering and Electronics, 2001, 23(11): 48–51.Google Scholar
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